Mastering Observability with OpenTelemetry

Learn how to leverage OpenTelemetry for actionable insights into the performance of your applications and services.

Introduction

• OpenTelemetry unveiled: Mastering modern observability
• What you should know
• Setting up your development environment
• Using the exercise files
• Getting to know the sample app
• Setting up the sandbox

1. Introduction to OpenTelemetry

• A brief history of monitoring and observability
• Understanding distributed tracing
• What is (auto) instrumentation?
• What is OpenTelemetry?
• Understand OpenTelemetry's architecture
• Important resources

2. Diving Into Tracing with OpenTelemetry

• Setting up the provided Node tracing module
• Instrumenting Node.js for tracing
• Instrumenting Python for tracing
• Introducing Jaeger
• Running Jaeger in Docker
• Exporting spans to Jaeger
• Analyzing traces with Jaeger
• Triage and manual instrumentation
• Finding the root cause in Jaeger

3. Using the OpenTelemetry Collector

• Introduction to the OpenTelemetry Collector
• A primer on sampling
• The goal for using the OpenTelemetry Collector
• Installing a local Collector
• Collector configuration
• Debugging and zPages

4. Observability with Grafana

• Why Grafana?
• The goal for observability with Grafana
• Creating a Grafana Cloud account
• Setting up the Grafana Collector integration
• Analyzing trace data in Grafana

5. Collecting Metrics

• Metrics in OpenTelemetry
• Adding metrics instrumentation to your code
• Viewing metrics in Grafana

6. Collecting Logs

• Logging in OpenTelemetry
• Configuring Python for logging
• Viewing logs in Grafana

Conclusion

• Next steps